Keywords

Abstract

Introduction and objectives. Socioeconomic status is associated with cardiovascular mortality. The aims of this study were to investigate the association between socioeconomic status and its various indicators and the risk of acute myocardial infarction (AMI), and to determine whether any association found is independent of the presence of cardiovascular risk factors (CVRFs). Methods. Study cases were matched with controls by age, sex and year of recruitment. Cases were recruited from a hospital register and controls from cross-sectional studies of the general population. The socioeconomic status was determined from educational level and social class, as indicated by occupation. Self-reported data were collected on the presence of CVRFs. Results. The study included 1369 cases and controls. Both educational level and social class influenced AMI risk. Among non-manual workers, there was an inverse linear relationship between educational level and AMI risk independent of CVRFs: compared with university educated individuals, the odds ratio (OR) for an AMI among those with a high school education was 1.63 (95% confidence interval [CI], 1.16-2.3), and among those with an elementary school education, 3.88 (95% CI, 2.79-5.39). No association between educational level and AMI risk was observed in manual workers. However, the AMI risk was higher in manual workers than non-manual university educated workers: in those with an elementary school education, the increased risk (OR=2.09; 95% CI, 1.59-2.75) was independent of CVRFs. Conclusions. An association was found between socioeconomic status and AMI risk. The AMI risk was greatest in individuals with only an elementary school education, irrespective of CVRFs and social class, as indicated by occupation.

Article

INTRODUCTION

Cardiovascular disease is the main cause of death
worldwide, 30% of all causes of death.1 Ischaemic
cardiopathy is its most frequent expression and is
the main cause of individual death of the population
as a whole. Different studies have shown that there
is an inverse gradient between socioeconomic
position (SEP) and total and cardiovascular
morbidity and mortality.2-11 Recently the World
Health Organization published a report entitled "Closing the gap in a generation: health equity
through action on the social determinants of health" with the aim of promoting development and the
application of policies and social action directed to
achieving health equity.12 In this report we propose
3 types of action: to improve life conditions, attack
inequalities due to the distribution of power and
economic resources, and measure and understand
the issue of inequalities affecting health and assess
the impact of the action taken.

With reference to measuring and understanding
the problem of inequalities in health, there is
discussion as to which is the best indicator to
determine an individual's SEP. The classical most
frequently used indicators have been level of
education and social class based on occupation, but
it is not yet known how these indicators are related
so as to define the risk associated with the SEP3,11,13. On the other hand, the mechanisms that explain this
association are not defined either, although in some
studies this excess risk has been explained as due to
differences in the prevalence of cardiovascular risk factors.5,7,11 Many studies have been carried out on Anglo-Saxon populations in which the incidence
of cardiovascular disease is much greater than that
seen in countries of Southern Europe. Furthermore,
there are studies that indicate a greater association
between SEP and cardiovascular mortality in
Northern European countries.4 In Spain there are
no data on the relationship between SEP and risk of
acute myocardial infarction (AMI).

The objectives of this study were to determine if
there is an association between SEP and risk of AMI
in our population, learn how different indicators
interact and modulate the risk of AMI in association
with SEP and determine if the relationship between
SEP and risk of AMI is related to a greater prevalence
of cardiovascular risk factors.

METHODS

Design

Population-based case-control study paired by
sex, age, and year of recruitment, performed in 6
areas of the Province of Girona.

Study Population

The cases were patients with a first AMI, of 25 to
74 years of age, who were consecutively seen at the
Hospital Universitario Josep Trueta (Josep Trueta
University Hospital) of Girona, the area reference
hospital, during the period from 1994 to 2006. AMI
was diagnosed using the MONICA Study criteria
of the World Health Organization.14 Those patients
records that had no information on SEP were
excluded.

The controls matched (1:1) the cases in sex, age
(±3 years) and year of recruitment (±2 years). The
controls were chosen randomly from the participants
in three cross-sectional studies from the same
population of origin of the cases. The cross-sectional
studies were carried out during the years 1994-1996,
1999-2001, and 2003-2005. Those patients who had a
previous AMI were excluded and also those with no
information about the SEP. The rate of participation
in the three cross-sectional studies was greater than
72%. The method used has been explained in detail
in previous papers.15,16

The study protocol was approved by the local
ethics committee and all the participants signed an
informed consent to participate in the study.

Socioeconomic Position

The SEP was determined by social class based
on occupation and maximum educational level
achieved. The social and demographic variables were collected (age, sex, occupation, and educational
level) using standardized questionnaires. The social
class was categorized based on the occupation of
the participants following the recommendations of
the Sociedad Española de Epidemiología (Spanish
Society of Epidemiology) based on the Spanish
Classification of Occupations of 1994.17 Housewives
and those beloging to religious orders, or armed
forces were excluded. In the case of pensioners the
categorization was based on their last occupation.
Three categories of social class were created: I-II
(managerial staff, higher degrees, and technicians),
III (administrative staff, independent workers,
supervisors of skilled workers), IV-V (skilled, semi-skilled, and unskilled manual workers). In some
cases (interaction between different SEP indicators)
these 3 categories were regrouped as 2: non-manual
workers (social class I-II-III) and manual workers
(social class IV-V).

Three categories were defined according to the
highest educational level achieved: tertiary or
university studies, secondary studies, and primary
or lower studies.

Other Variables Collected

Standardized questionnaires were used to
collect information related to the prevalence of
cardiovascular risk factors. The subjects were
classified as smokers if they said they smoked at
least one cigarette a day during the previous year or
had given up smoking during the last 12 months, as
former smokers if they had given up more than 12
months ago and as non-smokers if they had never
smoked. The prevalence of hypertension, diabetes,
and dyslipidaemia was assessed by means of self-statements or the use of drugs to treat them.

The participants were weighed and measured
barefoot and in light clothing, and the body mass
index (BMI) was calculated based on weight
(kilograms) divided by height (meters) squared. Three
categories were defined according to BMI: normal
weight (BMI<25 kg/m2), overweight (BMI≥25 and
<30 kg/m2), and obesity (BMI≥30 kg/m2).

Statistical Analysis

Continuous variables were described using the
mean and standard deviation. For comparison of
continuous variables between groups, the Student
t test or variance analysis was used. Categorical
variables were expressed in percentages and the
c2 test was used to determine differences between
categories. Logistic regression was used for
multivariate analysis. Several models were defined
to analyze the association between SEP and risk
of AMI in which the independent variable was
level of education (3 categories) or social class (3
categories) adjusted by age and sex and subsequently
including cardiovascular risk factors in the model.
Furthermore, the interaction between the 2 SEP
indicators used was analyzed, and 6 groups were
defined according to level of education and 2
groups were defined according to social class based
on whether their occupation was manual or non-manual work. A P<.05 was considered statistically
significant.

RESULTS

In Figure 1 it is possible to see a diagram of the
registration, screening and inclusion of participants
in the study. Of the 2204 cases of AMI registered
during the study period, 212 were excluded because of previous AMI and 619 were excluded because
we had no data on their SEP. Of the 11 158
participants in the cross-sectional studies, 403 were
excluded because they had some form of ischemic
cardiopathy and 3317 were excluded because we had
no data on their SEP. Differences were seen between
cases and controls included and not included in
the study because we had no data on their SEP: a
larger number of cases and controls were excluded
than included, and there was a larger proportion of
women. Finally 1369 cases were matched with their
respective controls.

Table 1 shows the clinical characteristics,
social class and level of education of both groups.
Globally mean age was 58 (SD, 10), and 14.7%
of the participants were women. In the group of
patients with AMI there was a larger proportion of
individuals in the least favored classes (P=.002) and
with a level of education of primary studies or less
(P<.001). The patients with AMI also had a greater
prevalence of cardiovascular risk factors (P<.001),
except for obesity (P=.083).

The participants with a higher level of education
were younger than those with primary studies, they
were mostly men and they had a lower proportion
of hypertension, dyslipidemia, diabetes, overweight
and obesity (Table 2). The percentage of former
smokers increased with educational level (Table 2).
When differences were analyzed taking into account
social class, similar results were seen although there was no greater prevalence of dyslipidaemia and
diabetes in underprivileged classes nor differences
between groups in smoking habits (Table 3).

Table 4 shows the raw and adjusted odds ratio of
presenting an AMI according to level of education
and social class. The association between level of
education and risk of AMI had a linear and inverse
gradient that was independent of cardiovascular risk
factors.

Analyzing the 2 SEP indicators available in the
study and their relationship with AMI, we saw that
in the crude model there was significant interaction
between social class (P=.011) and level of education
(P<.001). Therefore, we carried out a stratified
analysis by social group, defining 2 groups based on
occupation (manual or non-manual) and analyzed
the association between level of education and AMI
risk in each group (Figure 2). In the group of non-manual workers we saw a clear linear association
between level of education and AMI risk that was
independent of cardiovascular risk factors. In
the group of manual workers, no association was
seen between level of education and risk of AMI,
although it was possible to observe an excess of risk
with respect to non-manual workers, with university
studies and odds ratios that ranged between 1.84 (95%
CI, 1.23-2.73) and 2.3 (95% CI, 1.8-2.91) according
to level of education. The excess of risk in manual
workers with university or secondary education
was no longer significant when it was adjusted for cardiovascular risk factors, but continued to be
statistically significant in the primary education
group.

Figure 2. Association between level of education and risk of AMI stratified by social class based on occupation. A: model 1, adjusted by age and sex.
B: model 2, adjusted by age, sex, diabetes, dyslipidemia, hypertension, smoking, and anthropometric measurements.

DISCUSSION

In our study we saw a linear inverse association
between SEP and the risk of AMI. Level of
education is inversely associated, and independent
of cardiovascular risk factors, with the risk of AMI
in the group of non-manual workers. However, the level of education is not associated with AMI risk
in manual workers. On the other hand, the group
of manual workers has a greater risk of AMI than
non-manual workers; this excess risk is related to
a greater prevalence of risk factors in the group of
individuals with secondary and university studies,
but it is independent of cardiovascular risk factors in
the population group with primary studies or less.

Several studies have analyzed and confirmed
the relationship between SEP and risk of suffering
cardiovascular events and global mortality.2-9,18-23 In Spain, the existence of an association between
level of education and cardiovascular and global
mortality has also been confirmed using mortality
data from the city of Barcelona during the period 1992-2003,10 although no data have been published
on the relationship with AMI.

On analyzing the relationship between different
indicators of SEP and risk of AMI, we saw that globally and in our population these two indicators
are closely correlated, although the relationship
between social class based on occupation and risk
of AMI did not have such a clear linear gradient
as the one seen in relation to level of education.
However, there was an interaction between level
of education and social class that modulated the
risk of suffering an AMI. In other populations an
interaction between these 2 indicators has already
been described in association with a healthy diet.24 These results suggest that both indicators provide
additional information to define risk associated with
SEP.

Many studies,3,5,6,11,25-27 also in Spain,28 have detected a greater prevalence of cardiovascular
risk factors in less favoured social classes. For this
reason, it has been suggested that the relationship
between SEP and risk of AMI could be mediated by
an accumulation of risk factors in underprivileged
groups.29,30 The results of our study, as in
others,7-9,31,32 suggest that both in manual workers
and in non-manual workers the association seen
between the group with a lower level of education
and the risk of AMI is independent of classical
cardiovascular risk factors. On the other hand,
the excess risk observed in manual workers with
secondary or university studies was mediated
by cardiovascular risk factors. These results are
relevant and suggest that in addition to classical
risk factors there may be other factors related to
level of education that could explain the excess
risk in these underprivileged classes. Among
these factors we could include family,8 work3,3 or
financial34 stress and the social class of the father35
and other social determinants of health such as
physical and social environments (safety and
violence, support and social cohesion or social
norms),36 which were not assessed in our study.
The level of education, as well as economic level,
also reflects important aspects of the formation of
a person during childhood, the process of learning
and skill acquisition which condition subsequent
decisions on life-style and attitudes related to
health.11,37

Another aspect that could influence this
association is related to equity of access to health
services. Differences in the accessibility of the
health system may condition inequalities of health
that account for a worse risk profile and greater
morbidity and mortality. In a study carried out in
Spain, a country where health care is universal and
free, it was seen that family income was inversely
associated with consultation of the family doctor,
and directly with consultation of specialists, but
was not associated with hospital admittance.38 This suggests that people with low socioeconomic levels
consult general physicians to obtain a solution to most of their health problems and that only a few
patients are sent to other more specialized care, and/
or that many consultations of general physicians are
not due to health problems, but reflect other social
needs.38 Although we could think that people of
underprivileged social classes receive less preventive
treatment that could account for the greater
prevalence of risk factors, the ICAR study carried
out in Spain in patients with ischemic cardiopathy
did not show any differences in this sense, at least in
relation to secondary prevention.39

During the last decades, the health authorities
and scientific societies have expended a lot of
effort on prevention of cardiovascular disease,
directing their efforts to control of cardiovascular
risk factors. However, and as the results of our
study would suggest, especially in the population
group with primary studies or less, cardiovascular
disease is also related to certain social issues that
include social inequalities due to economic income,
social exclusion, work instability, lack of social
support and lack of educational opportunities.40 In this context, the most recent European guidelines
establish that social factors must be taken into
account when designing comprehensive programs
for cardiovascular prevention.41 These general
guidelines should be specific for each population
and adapt to local conditions keeping in mind the
characteristics of the target population.

Study Characteristics and Limitations

One of the main characteristics of this study is its
population, since we consecutively registered all the
patients who were admitted for AMI to the reference
hospital of the area of interest. The controls are also
representative of the population of origin of the
cases. Having selected controls matched for age,
sex, and year of registration/recruitment allows us
to interpret the magnitude of the association of our
results as a relative risk.42

One of the limitations is that we were not able
to include more cases of AMI as some died before
reaching hospital. Another limitation of this study
is that we lacked information on occupation or
educational level which meant that we had to exclude
participants (for example, housewives, as we did
not have any information on the occupation of the
household wage earner). This group of participants
was older and there was a larger percentage of
women, most of them housewives older than the
ones included in study. The eldest group had a lower
socioeconomic level, so that by excluding some of
these cases we believe we favored the null hypothesis
and therefore the magnitude of the association
observed could be an under-estimation of the real
state of affairs.

Although we used self-statements made by the
study participants to determine the prevalence of
risk factors, a recent study has shown that self-stated variables have a high degree of concordance
with data registered in clinical histories.43

CONCLUSIONS

There is an inverse association between SEP and
the risk of suffering an AMI. Level of education and
social class based on occupation are indicators that
provide additional information. Level of education is
the indicator that captures excess risk associated with
SEP independently of prevalence of cardiovascular
risk factors, suggesting that in the subgroup of
population with a low level of education other social
health factors determine this excess risk.

ACKNOWLEDGMENTS

We wish to acknowledge all the participants and researchers of the REGICOR study without whom the
study would not have been possible. This project was
financed by the Spanish Ministry of Innovation and
Science, Carlos III Institute/FEDER (Red HERACLES
RD06/0009); the Health Research Fund (FIS 94/0539,
FIS96/0026-01, FIS 97/1117, FIS99/0655, FIS99/0013-01
and FIS 99/9342); and the Agencia de Gestión de Ayudas Universitarias y de Investigación de la Generalitat
de Catalunya (Agency for University Assistance and the
Research Agency of the Catalonian Government), (2009
SGR 1195).

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